Shaofei Jiang

PhD Student in Economics at UT Austin

I am a 5th year PhD student in Economics at the University of Texas at Austin. My research interests are information economics and game theory.

E-mail: shaofeij@utexas.edu

Research

Abstract: We study a disclosure game with a large evidence space. There is an unknown binary state. A sender observes a sequence of binary signals about the state and discloses a left truncation of the sequence to a receiver in order to convince him that the state is good. We focus on truth-leaning equilibria (cf. Hart et al. (2017)), where the sender discloses truthfully when doing so is optimal, and the receiver takes off-path messages at face value. In equilibrium, seemingly sub-optimal truncations are disclosed, and the disclosure contains the longest truncation that yields the maximal difference between the number of good and bad signals. We also study a general framework of disclosure games which is compatible with large evidence spaces and a wide range of disclosure technologies. We characterize the unique equilibrium value function of the sender and propose a method to construct truth-leaning equilibria for a broad class of games.

Abstract: Evidence games study situations where a sender persuades a receiver by selectively disclosing hard evidence about an unknown state of the world. Evidence games often have multiple equilibria. Hart et al. (2017) propose to focus on truth-leaning equilibria, i.e., perfect Bayesian equilibria where the sender discloses truthfully when indifferent, and the receiver takes off-path disclosure at face value. They show that a truth-leaning equilibrium is an equilibrium of a perturbed game where the sender has an infinitesimal reward for truth-telling. We show that, when the receiver's action space is finite, truth-leaning equilibrium may fail to exist, and it is not equivalent to equilibrium of the perturbed game. To restore existence, we introduce a disturbed game with a small uncertainty about the receiver's payoff. A purifiable equilibrium is a truth-leaning equilibrium in an infinitesimally disturbed game. It exists and features a simple characterization. A truth-leaning equilibrium that is also purifiable is an equilibrium of the perturbed game.

Abstract: I study a model of firm dynamics where a firm can invest in product quality and exert efforts to obtain good publicities. The market learns from good publicities without directly observing quality, investment, or efforts. I analyze the relationship between the firm's advertisement and investment incentives. I show that any equilibrium has a threshold structure: the firm invests and advertises when the market belief is low, only advertises for a range of intermediate beliefs, and does neither when the belief is high. I further study whether increased frequency of publicity opportunities will lead to increased investment, and how these results differ when the market learns from bad news.

Teaching

I was awarded this year's Outstanding Teaching Assistant Award by the Economics Department.

As instructor:

As teaching assistant:

  • Microeconomics II (PhD), for Prof. Caroline Thomas, UT Austin (2018-20) | Select TA session notes

  • Math for Economists (PhD), for Prof. Maxwell Stinchcombe, UT Austin (2019)

  • Probability & Statistics (PhD), for Prof. Maxwell Stinchcombe & Haiqing Xu, UT Austin (2017-18)

  • Macroeconomic Theory, for Prof. Felipe Schwartzman, UT Austin (2017)

  • Introduction to Microeconomics, for Prof. Thomas Wiseman, UT Austin (2016)

  • Applied Econometrics, for Prof. Wanchuan Lin, Peking University (2016)